Meta System Design Interview Questions
Practice 1,159 real Meta interview questions for 2026. Covers top categories — Coding & Algorithms, Analytics & Experimentation, Data Manipulation (SQL/Python), Behavioral & Leadership, and System Design — across Software Engineer, Data Scientist, Machine Learning Engineer, Data Engineer, and Product Manager roles. Real questions from actual interviews with detailed solutions. Expect a software-engineering-heavy loop: timed algorithmic coding (trees, arrays, graph/maze problems, delimiter/CSV parsing), system-design prompts like leaderboards, flight search and online-judge architectures, and an increasingly common AI-assisted coding round that mirrors real workflows. Data Scientist rounds emphasize product analytics and experimentation—designing tests, diagnosing spend drops and bots, evaluating unconnected content, and writing SQL for multi-account, seller, and vehicle metrics. Machine Learning Engineer questions skew toward recommender and ranking work (place and friend recommendation, sparse-matrix ops, linear-regression derivations, newsfeed dislike models). Data Engineers focus on data modeling, ETL, capacity calculations, reservations/utilization queries, and production SQL/Python tasks. For interview preparation, prioritize timed coding practice, system-design templates, rigorous SQL drills (joins/CTEs/aggregation), clear A/B-testing frameworks, and concise STAR behavioral stories tied to measurable impact.
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Resolve a team conflict decisively
Tell me about a time you resolved a significant conflict within a team under time pressure. Include: 1) the root causes (interests, incentives, commun...
Design and analyze a group-calls experiment
You are considering launching Group Video Calls. Answer all parts precisely; justify choices with pros/cons and formulas where relevant. 1) Clarify CT...
Explain background, team structure, and role fit
Answer the following in order: 1) Give a crisp 90‑second self‑introduction tailored to this role, emphasizing 1–2 quantifiable achievements most relev...
Identify non-table data for feature demand
Evaluate Demand for a New "Group Call" Feature Using Non-Table Data and Experiments Context You are a data scientist evaluating whether to invest in a...
Design and evaluate P2P payments in messaging
P2P Payments in a Large Messaging App — Design, Measurement, and Risk Plan You are a data scientist at an at-scale messaging platform evaluating a Ven...
Design a clustered notification experiment with guardrails
You work on a mobile travel app (think TripAdvisor-like) that will test a new push-notification policy recommending nearby attractions. Design a rigor...
Reflect on feedback and metric trade-offs
Describe a time you chose a simpler metric under tight time constraints and later received critical feedback that it was oversimplified (e.g., from a ...
Define composite success for search and test it
A new search feature is evaluated with two binary labels per query: relevancy=1/0 and accuracy=1/0. 1) Propose a composite success metric that uses th...
Design B2C chatbot success metrics and test plan
You own 'euro-chat', a B2C customer-support chatbot that aims to deflect agent contacts while preserving customer satisfaction. Design a rigorous succ...
Quantify launch decision with tests and guardrails
You will formalize the statistical decision rules for the Instagram button experiment described above. Given: baseline exploration rate (p0) = 0.15 pe...
Build dashboard; diagnose engagement–purchase gap
Build a Comprehensive Dashboard for the Shopping Tab (Organic Only) Context Assume the Shopping tab is an in-app surface for organic product discovery...
Design an A/B test for WhatsApp call reliability
A/B Test Design: Adaptive Codec for Unstable Networks (WhatsApp Calling) Context You join the Calling organization. A PM proposes enabling an adaptive...
Design a small-sample launch experiment in Europe
Launch Test Design: Early-Access EU Businesses Context You have an early-access pool of 1,200 EU businesses for a new chat subscription offering. Chat...
Define success metrics and guardrails for B2B chat
Define a Success-Measurement Plan for a New EU B2C Chat Subscription You are launching a paid business-to-customer chat subscription in the EU. Design...
Choose robust metrics for skewed comments
Robust central tendency and inference for zero‑inflated, heavy‑tailed counts You are evaluating an A/B test on per‑user daily comment counts. The outc...
Analyze regression to mean in heavy-tailed shares
Cohort Dynamics of a Right-Skewed Daily Shares Metric Context - You have a right-skewed metric: daily shares per user, with a long tail. - On Day 1, y...
Compute conditional occupancy across two rooms
Probability and Bayes Update: Two Rooms Setup There are two rooms. Prior over occupancy states: - With probability 1/3: both rooms are occupied. - Wit...
Derive expected meetings given nonempty room
Zero-Truncated Binomial: Random Room Assignment Setup - There are N rooms labeled 1, 2, ..., N. - K meetings are scheduled; each meeting independently...
Compare two ad insertion strategies
Ad Insertion Strategies for a 100-Post Feed You are evaluating two ad-insertion strategies on a feed with 100 posts: - Strategy A (Stochastic): Indepe...
Model user-level ad impression allocation
Random Assignment of Ad Impressions to Users Context - There are X distinct users and Y ad impressions (X ≥ 1, Y ≥ 0 integers). - Each impression is i...